Evaluating the Observed Log-Likelihood Function in Two-Level Structural Equation Modeling with Missing Data: From Formulas to R Code

Autor: Yves Rosseel
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Psych, Vol 3, Iss 2, Pp 197-232 (2021)
Druh dokumentu: article
ISSN: 2624-8611
DOI: 10.3390/psych3020017
Popis: This paper discusses maximum likelihood estimation for two-level structural equation models when data are missing at random at both levels. Building on existing literature, a computationally efficient expression is derived to evaluate the observed log-likelihood. Unlike previous work, the expression is valid for the special case where the model implied variance–covariance matrix at the between level is singular. Next, the log-likelihood function is translated to R code. A sequence of R scripts is presented, starting from a naive implementation and ending at the final implementation as found in the lavaan package. Along the way, various computational tips and tricks are given.
Databáze: Directory of Open Access Journals